Health and Development Survey 1993DDI_TZA_1993_HRDS_v01_M
World Bank, Living Standard Measurement Study (LSMS)
2010-06-29Metadata EditorVersion 1.1 (April 2011).TZA_1993_HRDS_v01_MHuman Resource Development Survey 1993HRDS 1993TZA_1993_HRDS_v01_MUniversity of Dar es SalaamThe World BankMetadata EditorBritish Overseas Development AdministrationGovernment of JapanWorld BankLSMS Data ManagerLiving Standards Measurement Study [hh/lsms]The objectives of the survey were to provide information regarding the following:
a. Household use of, and expenditure patterns for, social services;
b. Reasons for low levels of household investment in education and health services for children;
c. The distribution of the benefits of public spending for social services and how to improve targeting;
d. Households' evaluation of the social services available to them;
e. The potential for demand-side interventions to increase human capital investment directly (especially for girls and the poor); and
f. The feasibility of repeated national monitoring surveys to assess the impact of future Bank and government projects in the social sectors, and to increase Tanzania's capacity to perform household survey work.TanzaniaNational coverageSample survey data [ssd]The main objective of the survey was to obtain data on the use of, and spending on, the social sectors. The primary emphasis was on education and health--the areas in which the major gaps in availability of data were identified. The survey was divided into five major components, each of which was further subdivided, as described below:
I. Individual Questionnaire
A. Household Roster;
B. Information on parents of children between 7 and 15 years of age;
C. Information on the utilization of, and spending on, education services;
D. Information on the utilization of health services for those reported ill in the month previous to the interview;
E. Information on the utilization of, and spending on, prenatal care, delivery, and family planning.
II. Contingent Valuation Questions on:
A. Primary Health Facility (includes modules allowing respondents to assess desired characteristics of facilities, to reveal their willingness to pay for health services, and to provide information on the available health care facilities);
B. Primary Education Facility (includes modules allowing respondents to assess desired characteristics of schools and curriculum, to reveal their willingness to pay for education services, and to provide information on the available schools and curriculum);
C. Demand for Child Spacing;
D. Envisaged, Required Income Level.
III. Household Questionnaire
A. Land and livestock ownership;
B. Household income and economic activities;
C. Annual expenditures;
D. Monthly expenditures;
E. Weekly expenditures;
F. Housing characteristics and expenditures;
G. Mortality: deaths in the last 12 months.
IV. Community Price Questionnaire
V. Cognitive Test:Sample size is 5,184 households
The HRDS is national in scope and uses all the 222 clusters of the National Master Sample (NMS) maintained by the Bureau of Statistics as its sampling frame.4 Two NMS clusters were not surveyed because of weather conditions. For example, Nyamburi village in the Mara region was inaccessible. Heavy rains had washed away a bridge 8 kms (14 miles) from the village. All household surveys conducted by the Bureau of Statistics (e.g. Agricultural Sample Survey since 1986/87, Labor Force Survey in 1990/91) have used the framework of the NMS. This permits obtaining estimates at the national level and by area: rural, Dar es Salaam (DSM), and other urban towns. The current NMS covers 222 clusters: 100 rural villages representing the rural areas, and 122 Enumeration Areas (EAs) representing the urban areas. Fifty-two EAs are from the capital city, itself, 40 EAs are from the nine municipalities (Arusha, Dodoma, Moshi, Tanga, Morogoro, Iringa, Mbeya, Tabora, and Mwanza), and 10 EAs are from the remaining regional headquarters.
Selection of households and non-response.
Household selection was done in the field. In each cluster the team supervisor would first obtain the list of ten-cell leaders from the local authorities, and then, from each ten cell-leader, the list of households belonging to his/her cell. Each household was assigned a unique number, and then, using a table of random numbers, randomly selected. In each cluster, a list of about 30 households was then obtained, the last households in the list being alternates. With the collaboration of local authorities, the field workers were able to have an almost 100 percent reponse rate, except for the cases in which no member of the household was present for intervieing, and returning to the household was not feasible. Refusals to cooperate were rare. In those cases--absent households or refusals--, new households were drawn from the list of alternates.
The survey covered a total of 4,953 households in the 20 regions of Mainland Tanzania: 2,135 rural and 2,818 urban (see Table 1). In a second stage, the survey was extended to Zanzibar, where 230 households, in 24 clusters, were interviewed.
Region / Rural / Urban / Total
Dodoma / 100 / 80 / 180
Arusha / 118 / 121 / 239
Kilimanjaro / 124 / 154 / 278
Tanga / 132 / 167 / 299
Morogoro / 88 / 120 / 208
Coast / 79 / 88 / 167
Dar es Salaam / 0 / 1127 / 1127
Lindi / 84 / 50 / 134
Mtwara / 114 / 44 / 158
Ruvuma / 69 / 49 / 118
Iringa / 124 / 128 / 252
Mbeya / 174 / 153 / 327
Singida / 82 / 41 / 123
Tabora / 99 / 72 / 171
Rukwa / 59 / 56 / 115
Kigoma / 83 / 35 / 118
Shinyanga / 153 / 54 / 207
Kagera / 193 / 24 / 217
Mwanza / 163 / 192 / 355
Mara / 97 / 63 / 160
Mainland Tanzania / 2135 / 2818 / 4953
Zanzibar / 127 / 104 / 231Face-to-face [f2f]Development of Survey Instrument.
The first draft of the household survey was developed in English in July, 1993. Training of enumerators, based on this draft, began on August 2, 1993. The month of August was devoted to training the enumerators and pre-testing the questionnaire. The first pre-test of the questionnaire took place in mid-August. The household questionnaire was almost completely precoded to eliminate coding errors and time delays. A category labeled "other: specify" was added to several questions. For those questions for which answers were not mutually exclusive, we precoded them with letters, rather than numbers, to allow for unambiguously coding of multiple answers. To minimize nonsampling errors, the questionnaire was in a form that reduced to a minimum the number of decisions required of interviewers while in the field. In anticipation of pages becoming detached from the questionnaire, every page contained a space for the household number and the last digit of the cluster code. Despite the fact that questions were written exactly as they were supposed to be asked by the interviewer, interviewers were granted some flexibility to give the interview greater semblance to a conversation, rather than an inquisition.
Pre-Test of Questionnaire.
The "pre-pre-test" of the questionnaire (August 16, 1993) was done only to discern whether the questions were understood, how long the administration of the survey required, whether all responses had been anticipated, which sections needed to be stressed during the training, etc. In this pre-pre-test, each questionnaire required an average of 4 hours to complete, far longer than the planned 1.5 hour maximum. The survey was consequently shortened and streamlined.
The true pre-test was conducted in two different types of clusters: Ubungo ward in DSM (urban) and Kibaha in the Coast Region (rural) over a period of two days. We chose these clusters because they are representative of two distinct groups, so a broader spectrum of answers and problems with the instrument could be anticipated. In the pre-test each questionnaire required an average of 2.5 hours. After a couple weeks of interviewing, the enumerators became more familiar with the instrument, resulting in their spending an average of 1.5 to 2 hours per questionnaire.
During the pre-test, each supervisor was asked to comment on each interview. The supervisor was asked to pay special attention to questions that seemed to make the respondent uncomfortable, that the respondent had difficulty understanding, or that the respondent seemed to dislike. The supervisor also evaluated which sections seemed to go slowly, had the most difficult questions, or provided insufficient opportunity for a complete response.
Revision of questionnaire.
Given the results of the two pre-tests, several areas for improvement in the questionnaire were identified. Perhaps most importantly, the willingness-to-pay amounts were adjusted. The sample distributions of the maximum willingness-to-pay questions were analyzed, and, based on that analysis, we decided to change some of the values. For example, in the child spacing question, the "pay Tsh 1,000" responses unexpectedly accounted for a large share of the bids. Thus, we provided the option of paying more by introducing "pay Tsh 50,000" and "pay Tsh 25,000" as answer choices. For the other contigent valuation sections--health and education--the first pre-test determined that there was also a large lumping of responses at the high end of the scale. We adjusted the ranges accordingly, although there remains some lumping at the high end in the final data.
We also changed the order of the sections. Based on the pre-test and judgment of the field workers, we decided to first ask the questions in the individual section, then the contigent valuation questions, then the household questions. Because the respondents enjoyed the contigent valuation questions so much, this decision helped increase interest in the questionnaire and re-energized the respondent before proceeding with the household questions--the last part of the questionnaire. The final survey instrument, incorporating all of the changes dictated by the pre-tests and other expert advice, was completed on September 12, 1993.
Translation.
Translation of the survey instrument was a joint effort of the enumerators and supervisors. Given the specific characteristics of the Kswahili language, this was a much better approach than asking one translator to translate from English to Kswahili, and another one to translate from Kswahili to English. The "group" translation, involving those who would ask the questions, was intended to avoid different interpretations of the same question and achieve uniformity. In this way the enumerators were able to better convey the message/objective of each question.
The majority of the interviews were conducted in swahili. In very few cases, because no one in the selected household could speak swahili, the need arose to use interpreters.
Our initial plan called for the field work to start no later than August 29. However, unforeseen circumstances, including both financial and logistical problems, delayed the first field trip. Both the money and the materials were available by September 6, and five of the six teams left for Tanga region on that day. Initially we had planned to have the sixth team based full-time in Dar es Salaam; however, tighter time constraints imposed by the above and subsequent delays eventually made it necessary to send the sixth team into the field as well, as detailed below.
Description of questionnaires
The main objective of the survey was to obtain data on the use of, and spending on, the social sectors. The primary emphasis was on education and health--the areas in which the major gaps in availability of data were identified. The survey was divided into five major components, each of which was further subdivided, as described below:
I. Individual Questionnaire
A. Household Roster;
B. Information on parents of children between 7 and 15 years of age;
C. Information on the utilization of, and spending on, education services;
D. Information on the utilization of health services for those reported ill in the month previous to the interview;
E. Information on the utilization of, and spending on, prenatal care, delivery, and family planning.
II. Contingent Valuation Questions on:
A. Primary Health Facility (includes modules allowing respondents to assess desired characteristics of facilities, to reveal their willingness to pay for health services, and to provide information on the available health care facilities);
B. Primary Education Facility (includes modules allowing respondents to assess desired characteristics of schools and curriculum, to reveal their willingness to pay for education services, and to provide information on the available schools and curriculum);
C. Demand for Child Spacing;
D. Envisaged, Required Income Level.
III. Household Questionnaire
A. Land and livestock ownership;
B. Household income and economic activities;
C. Annual expenditures;
D. Monthly expenditures;
E. Weekly expenditures;
F. Housing characteristics and expenditures;
G. Mortality: deaths in the last 12 months.
IV. Community Price Questionnaire
V. Cognitive Test:
The design of the questionnaire took advantage of the huge volume of work done on household questionnaires over the past decade. The next paragraphs highlight areas in which this survey is different from the Social Dimensions of Adjustment (see Delaine et al. 1992) or Living Standard Measurement-type of surveys (e.g. Ainsworth et al. 1992; Grosh 1991). Where appropriate, a summary of the reasons for the difference in approach is also presented.
The Yellow Card. A yellow-colored Household Roster card was included in the questionnaire. The interviewer had to copy some of the information--age, gender, and name--from the household roster onto this yellow card. The removable Household roster card was then used throughout the rest of the questionnaire for reference as to which members of the household were eligible for particular sections and what their ID numbers were.
Income Questions. It was decided that our survey, unlike the majority of the surveys we reviewed, would not include data to be used to estimate income levels. Gathering complete and accurate income data is a very time-consuming activity in countries where few receive wages and the majority are self-employed and engaged in non-market activities. In analysis, income questions are difficult to use; monetary incomes are often calculated to be negative; and, when much of the sample works outside the formal market economy, these problems are compounded. Given our time and budget constraints it was not logical for us to try to measure income.
We did include a few questions about sources of income. In this section, our objective was not to gather the information necessary to estimate income levels, but rather to ascertain the main economic activities in which the household engaged, and how the household ranked them in order of importance. For those growing crops, we wanted to establish the relative importance of each crop and the proportion of it that was marketed.
Expenditures Section. The three principal issues which had to be resolved regarding the expenditure section were as follows:
(i) How to organize the expenditures in terms of levels of observation: individuals or households, and the recall period;
(ii) Whether to split consumption expenditure and consumption of home production, or to ask them in the same question; and
(iii) How to take into account seasonality of food consumption.
Accurate and complete measurement of expenditures is essential. To maximize the accuracy of the information gathered, different types of expenditures were organized into different levels of observation, depending on the consumption item for which we were measuring expenditures. For example, better estimates of consumption are likely to be obtained by adapting the period of recall to the frequency of purchasing the good. Accordingly food expenditures had a week-long recall period, while education expenditures had a one-year recall period. For some items, we gathered information at the individual level- -e.g. education and health--and for some, at the household level--e.g. housing and utilities. For food items, we split consumption expenditure and consumption of home production. For items such as education, for which expenditures are more likely to be cash expenditures, we did not split them. However, we explicitly included the following instructions with the expenditure questions: "Please include contributions of labor and other non-cash items, which we will convert to shillings."
To address the problem posed by seasonality of consumption, we phrased the question as "During a typical week this past year, did anyone in this household acquire or spend money on..." Also it must be kept in mind that not all consumption expenditures are recorded in Part 3, Sections C, D, and E of the Consumption Section. Expenditures on education can be obtained from Section 1, Part C: Schooling, while housing expenditures were included in Section 3, Part F: Housing.
The survey asked only a few questions on ownership of durables and none regarding their acquisition cost or present value. There is evidence from Grosh, Zhao, and Jeancard (1995) that information on durables does not change the results of welfare ranking. This is another area in which we chose to shorten the questionnaire and the length of interview. 10. The Contigent Valuation Questions. One of the distinguishing features of the HRDS survey is the use of contigent valuation questions to better understand households' perception and valuation of some services available to them, which characteristics they value the most, and how far actual levels of provision are from desired levels. A three-step process was followed. In the first step, the respondent was given 20 chips (or shillings), representing a budget constraint. The enumerator then showed him or her a card with 5 pictures, representing 5 characteristics of a health facility (or of a primary school). The respondent was asked to allocate the 20 shillings among the 5 characteristics. In the second step, the enumerator asked how much the respondent was willing to pay for a visit to a health facility--or, in the case of education, for one year of tuition in a primary school--that matched the most important characteristics for the respondent. In the third and final step, the respondent was asked to characterize the closest health facility (and closest primary school) in terms of the five characteristics that he/she was previously asked to rank. This information should provide a picture of what households consider important in primary health and education services, and of how well the available facilities meet the household's desires. We tried to select characteristics that designers of health and education services tend to emphasize as important. For health, we mixed characteristics of public and private goods.
Respondent Rules. Different respondents were chosen for different sections to increase accuracy. For some topics, information from proxy or household respondents will be less accurate or less applicable (e.g. the contigent valuation questions on child spacing from a 10-year-old boy). In the header on each page of the questionnaire, there is a space to identify the respondent. This information can be useful for some types of analysis in which it is important to know characteristics of the specific respondent. In the introduction to each section, the preferred respondent is explicitly stated. Accordingly, for Section 1, Part A, the head of the household is the preferred respondent; but in Part D, the preferred respondent is "Each eligible individual, with assistance of the head of household if necessary."
The Community Questionnaire. We asked community questions to all selected households in a cluster because of the statistical principle that multiple answers to the same question provide better information, on average, than asking only a single "principal informant" these questions. Also, for some questions--e.g. distance to the closest village health center--it is important to obtain answers from each household. In some rural clusters in Tanzania, houses can be 15 miles apart. Therefore important intercluster inequalities may be neglected if not all households are questioned. The price questions, because they do not vary much across households in a cluster, were answered either by a principal respondent or through inspection in the local markets or shops.First "Field Trip."
From September 6 through September 10, 1993 an experimental survey trip was conducted. Five teams went to Tanga region, and one team remained in Dar-es-Salaam. The major findings from this trip were as follows:
a. On average each questionnaire required 2.5 hours to complete. The following were fixed time costs of entering each cluster: identification of boundaries in the case of urban clusters; authorization from the local authorities; identification of the ten cell leaders; listing; identification and selection of the households; and required travel to each home. The teams could then proceed with the interviews. In total, each enumerator could
perform only about 3 interviews per day; in the rural villages it became dark after six p.m., and no electricity was available.
b. Given the length of the questionnaire and our experience in the field, we decided to drop the section entitled "TIME USE DURING SCHOOL YEAR." This section proved to be very time-consuming, and respondents became tired quickly, which was likely to have adverse effects on the following section of the questionnaire, "ACUTE ILLNESSES."
c. After this first week of "real" field work, some fine tuning in the survey instrument was necessary. Also, a need to expose the enumerators to further training was recognized, as several major areas of weakness became evident. At the same time, we started producing 4,500 copies of the final questionnaire. Once again a delay in the transfer of funds delayed the start of field work. The first tranche of the payment was not received until September 18. Accordingly, all the contracts were modified, and the field work was replanned to start on September 19.
d. Additional Training. Four major problems surfaced which indicated a need for more training. The enumerators did not fully understand the following concepts:
(i) In-kind income/expenditure. Subsistence farmers with no other economic activity would appear in the completed questionnaire as having no source of income, and as having no expenditure on those items for which no cash payment had actually been made.
(ii) Household membership and how to report expenditures for members who had also been "members" of other households within the previous 12 months (e.g. newlyweds).
(iii) Direct sponsorship and indirect subsidies to students in the education section.
(iv) Use of the yellow card.
e. The enumerators received further training (September 12 through September 16). In reviewing the questionnaires, we also determined that it was necessary to reinterview some of the households.
f. The performance of one supervisor and two enumerators did not meet our quality standards, and they were dismissed. This fact, together with the loss of one supervisor for health reasons, required replanning of the field work. However, the dismissal of the supervisor and enumerators, combined with the promotion of four enumerators to assistant supervisor positions, positively affected the motivation and performance of the whole team.
Field Trip Preparation.
Initially the field work team was composed of 6 supervisors and 33 enumerators. After the Tanga trip, the team was reduced to 4 supervisors and 31 enumerators. This final team of 31 enumerators comprised students and recent graduates from the University of Dar es Salaam, who were primarily economics and business majors. 19. Given the constraint that 21 of the 31 enumerators were students who needed to be back in Dar es Salaam no later than October 12, the following was decided:
(i) All teams would work outside Dar es Salaam for the period of September 18 through October 12. Initially we had planned that 1 team (comprising 8 enumerators) would interview in Dar es Salaam, while the other 5 teams would go upcountry.
(ii) After the students returned from the countryside, they would start interviewing in Dar es Salaam, on a part-time basis, while the 10 graduate enumerators finished the clusters outside Dar es Salaam.
(iii) Each 2 supervisors had 15 or 16 enumerators, rather than 5, as initially planned. As this imposed an additional burden on the supervisors, 4 enumerators, based on their superb performance during the first week of field work, were promoted to Assistant Supervisors. Other than interviewing, they were responsible for a preliminary check of each questionnaire for mistakes, unanswered questions, wrong skip rules, inconsistencies, etc., before the supervisor proceeded with the final check. Nonetheless, the final word on the quality of the questionnaire remained in the supervisors' hands. Given the logistics of the field work, it was essential to have each and every questionnaire thoroughly checked before the team left the cluster.
Survey Preparation.
In each cluster the research team needed to obtain permission from the authorities before beginning the interviews. Previous to the start of the field work, we requested permission from the Government Statistician to conduct interviews using the NMS clusters as the sampling framework. The research clearance was obtained from the university rather than from the government because the team that carried out the field work was from the university. There were certain procedures that had to be followed before beginning the interviews. First, in each region, one had to obtain permission from the regional headquarters to conduct the interviews. Second, the district authorities had to issue a research clearance, to be later presented to the ward secretary. Often, the ward secretary introduced the team to the village authorities. In the villages, the teams were introduced to the households either by the village secretary or by the ten-cell leaders.
Survey Materials.
Each enumerator was given an "Interviewer's Manual," two sets of cards and 20 chips for the Bidding Games, and a set of supplies consisting of a briefcase, pencils, eraser, notebook, calculator, red pen, clip board, and binder clips. Also, each enumerator had a supply of the cognitive tests, yellow cards with and without printed ID numbers, and blank questionnaires. It was the enumerator's responsibility to administer the household questionnaire and the cognitive test.
The Zanzibar Household Survey.
The Revolutionary Government of Zanzibar expressed a desire to have a Household Survey conducted in Zanzibar so that they might have the same type of information that had been gathered for the Mainland. The early experience with the Tanzania Household Survey and the more recent experience with the additional field work in Zanzibar helped us to conclude that many of the time costs are fixed--traveling to the site, securing clearance from the appropriate authorities, training the interviewers, etc. Once the interviewers are familiar with the survey and the supervisors are familiar with the mechanics of the work, the new survey can be conducted quickly. In fewer than 10 days of field work, a group of six experienced interviewers, one supervisor, and a member of the Bureau of Statistics of the Republic of Zanzibar interviewed 230 households in 24 different clusters.The main mission of the supervisor was to check the work of the other team members at all levels, guarantee that interviews in the field proceeded satisfactorily, maintain high quality standards, review the completed questionnaires, and reinterview a sub-sample of the households. As the number of completed questionnaires was viewed as an indicator of interviewer performance, it was conceivable that interviewers would indicate an incorrect response to questions requiring follow-up questions in order to expedite the process. For example, if the household had no income from crop production, then the interviewer would not need to ask questions regarding the type of crop grown. If a household were revisited, the upervisor
would use a "mini-questionnaire," containing a set of such questions. Every household questionnaire was checked by the supervisor after the interview was completed. At the end of each day, the supervisor and the enumerators discussed particular cases covered, problems faced, questions that proved to be difficult, etc. The supervisors' other tasks included arranging logistics, random selection of households in each cluster, assignment of households to each enumerator, obtaining clearance from several administrative layers, and completion of the price questionnaire. To perform these tasks, each supervisor received, in addition to materials received by the enumerator, a Supervisor's Logbook . It included the following:
i. Supervisor's Manual.
ii. Price questionnaire to be administered in each cluster by the Supervisor.
iii. Sample Design and Selection:
(a) Selection of the clusters was based on the National Master Sample maintained by the Bureau of Statistics (1988 Census). Each supervisor was provided with a set of maps for each cluster.
(b) Within each cluster, households were randomly sampled. Instructions to sample households were given to each team supervisor. These instructions included a set of random numbers tables.
iv. Forms to re-interview households.
v. Forms to be completed for each cluster with the population of the cluster and its number of households. This information is essential to construct the weights to be used in the analysis.
vi. General set of instructions on how to assign a unique identifier to each household.
vii. For the first week of the field work, the supervisor's logbook also included a spreadsheet in which the results from the contigent valuation questions were to be entered.
After each interview the supervisor was expected to spend some time checking and editing each questionnaire. This is particularly important in the rural areas, and in urban clusters far from Dar es Salaam, where the costs of returning to the cluster are high. The household questionnaire even included one page (page 4B) for the supervisor's check. We noticed that, in some questionnaires, the supervisor's check was not very strict. The majority of mistakes that we handled during the data cleaning and coding phase could have been avoided had the supervisor been more careful with the checking of each questionnaire in the field. However, we will now be able to improve the manuals by specifically noting many of the problems we found. Data entry in the field, or close to the clusters, would probably reduce such problems tremendously. Also, contrary to what was planned the supervisors did not reinterview any of the households.In each cluster, between 20 and 25 households were targeted to be interviewed.5 These households were randomly selected. For a household belonging to village i, the household sampling weight (factor from household level to the national level) is defined according to the following expression:
Wh = Wi * (1 / Ni)
where Ni gives the sample size in village i, and Wi is the NMS village weight (factor that expands from the cluster level to the national level).Data entry.
Two possible firms in Tanzania were identified to perform the data entry. Both were asked to present cost estimates. Based on the cost estimates and the conditions proposed by each firm, it was decided to contract the services of Dr. Swai at the Data Processing Center at the Muhimbili Hospital. The team was composed of one supervisor, 12 data entry people working in shifts, and 1 liaison at the World Bank Resident Mission in Dar es Salaam.
At the start of the field work, the interviewing and data entry were nearly simultaneous. Each team was in charge of mailing the completed questionnaires to the Resident Mission, which then delivered them to the supervisor. However, because the field work slowed down after classes began (only the 10 non-student enumerators continued interviewing) and only returned to full speed in mid-December (again with a full team of 31 interviewers), the flow of questionnaires was not nearly as smooth as planned.11 We had great difficulty keeping track of the survey effort during November and December due to communication problems between the nodes: the field, the data entry people, the Resident Mission, and Washington. Given that the household survey was an essential building block for the Social Sector Review, and because breakdowns in the data entry system caused grave concern about the timeliness and quality of the data to be made available to us, we decided to have the questionnaires shipped to the U.S. Several possible firms were identified, asked to present cost estimates, and to propose a schedule of activities. Based on the information provided, a contract was awarded to Office Remedies. To minimize data entry mistakes, the data were entered twice, by different people. This ensures over 99% accuracy.
As previously mentioned, the questionnaire that was used during the Tanga trip included an additional question on "TIME USE DURING SCHOOL YEAR." This information was entered at the World Bank headquarters using the SURVEY Program.Major problems with the Survey:
i. Delay in receiving funds and materials from Washington . We operated in the nearly impossible situation of raising money to pay for the survey while it was underway. In addition, the time schedule placed incredible stress on World Bank procurement and payment mechanisms. If we had had more time, all of these processes could have been arranged well in advance. As this was not the case, it was all done on an emergency basis. We caused incredible stress to the system, everyone around us, and ourselves. The delays were usually short, but they caused a few important and avoidable delays in the survey. The goodwill and flexibility of our colleagues, especially of Professor Amani, made it possible to succeed nearly on schedule. However, none of us would advocate repeating the experience in this manner.
iii. Price Questionnaires. We only obtained price questionnaires for 70 clusters, out of 222 planned. For the remaining clusters, the prices questionnaires were either lost or not completed. The remaining data still seem useful to obtain some information on price variation within and across different regions. iv. Two Forms. During the first week of the field-work we used a questionnaire that included a section on time usage for some members of the household, and had a different ordering of questions in other sections. The existence of two forms caused additional problems during the data entry phase.World Bank LSMSThe researcher will refer to the 1993 Tanzania Human Resources Development Survey as the source of the information in all publications, conference papers, and manuscripts with the following statement "The data used in this paper come from a nationally representative survey of 5,000 households in Tanzania. The survey was a joint effort undertaken by the Department of Economics of the University of Dar es Salaam, the Government of Tanzania, and the World Bank, and was funded by the World Bank, the Government of Japan, and the British Overseas Development Agency."In receiving these data it is recognized that the data are supplied for use within my organization, and I agree to the following stipulations as conditions for the use of the data:
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3. The researcher will refer to the 1993 Tanzania Human Resources Development Survey as the source of the information in all publications, conference papers, and manuscripts with the following statement "The data used in this paper come from a nationally representative survey of 5,000 households in Tanzania. The survey was a joint effort undertaken by the Department of Economics of the University of Dar es Salaam, the Government of Tanzania, and the World Bank, and was funded by the World Bank, the Government of Japan, and the British Overseas Development Agency." At the same time, the World Bank is not responsable for the estimations reported by the analyst(s).
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5. The database cannot be used for commercial ends, nor can it be sold.The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.DISTRICT.NSDstat215110Nesstar 200801HR.NSDstat518411Nesstar 200801HR1.NSDstat2991427Nesstar 200801HR2.NSDstat702611Nesstar 200801HR3.NSDstat1251955Nesstar 200801HR4.NSDstat517550Nesstar 200801HR5.NSDstat718958Nesstar 200801HR6.NSDstat5184100Nesstar 200801HR7.NSDstat5184141Nesstar 200801HR8.NSDstat5184144Nesstar 200801HR9.NSDstat758616Nesstar 200801HR10.NSDstat466511Nesstar 200801HR11.NSDstat229905Nesstar 200801HR12.NSDstat1315646Nesstar 200801HR13.NSDstat645517Nesstar 200801HR14.NSDstat518466Nesstar 200801HR15.NSDstat32917Nesstar 200801HR16.NSDstat80818Nesstar 200801HR17.NSDstat10483Nesstar 200801infant mortality rate per 1,0002150-9127.944.74254.73cluster id215012009203151035083505.1777012677.24Region id215011021031141359667508597105119121313614915516517111891916206district id2150120550.65656.119population according to the 882150330541208914304250.191198923.507educ-personal emolumts, 1990-912150022094061207.91645442.433educ-other charges, 1990-91215008591817158.77714254.634educ-total charges, 1990-912150026212178366.61956821.021health-personal emolumnts, 1990215004116013618.62810870.242health-other charges, 1990-91215004020315099.50711720.671health,total charges, 1990-91215006819228718.04220701.85water & sanitat, prsnl emol, 1921500489231917.1533891.059water & sanitat, other chrgs, 121500252573552.4795145.952water & sanitat, total chrgs, 121500588675469.6427637.193social sectors, prsnl emol, 1992150024710076743.61954090.227social sectors, othr chrgs, 1992150010770135810.62327042.695social sectors, total chrgs, 1921500312773112554.2677723.129social sectors, other, 1990-91215001756958644.83718082.189social sectors, grand total,19921500351389121199.05683825.301total revenue, estimated, 1990-2150020148637273.60937038.21total revenue, actual, 1990-91215008572828348.93523902.92educ-personal emolumts, 1992-93215018587849865316873.372299291.11educ-other charges, 1992-9321505512863023454.00520375.806educ-total charges, 1992-93215021868902760340327.177316070.142health-personal emolumnts, 19922150751729905995453.279112997.274health-other charges, 1992-93215013804694720731.29315302.428health,total charges, 1992-93215012654342328116184.484125690.182water & sanitat, prsnl emol, 1921500118664782.0884281.525water& sanitat, other chrgs, 1921500202832631.5953562.307water & sanitat, total chrgs, 121500282667413.4196122.64social sectors, prsnl emol, 1992150268831160411417108.433414613.834social sectors, othr chrgs, 1992150572916646246816.77235742.132social sectors, total chrgs, 192150361981258462463925.214444056.547number of wards215075329.01414.592land area, sq km215028475276035.0097976.718number of villages2150-921673.34956.943number of district roads2150-91162238.702189.422number of feeder roads2150-97364583.27773.129water service schemes-gravity2150-9834.413.445water service schemes-motor2150-9967.74913.096water service schemes-other2150-9708117.763131.557population with clean water2150262474450173678.395176261.636number of primary schools215013272119.40958.228numbr of class rooms21509739491374.931452.713permanent class rooms2150-93000938.6141155.93temporary class rooms2150-91090390.279358.116number of teachers2150-953462051.2331867.349pupils eligible for primary sch2150-97103124369.34426701.766number of pupils in std i2150-94131314048.96315366.231number of pupils in std vii2150-9225768173.7028125.016pupils sitting for psle2150-9219967713.2288071.379pupils selected for form i2150-92570755.4651004.503number of schools2150-9302.67416.039government owned schools2150-914-3.0477.379privately owned schools2150-9220.53512.817other educational institutions2150-915-8.5533.251number of hospitals215005174248331471350number of health facilities21500121202383444325865675number of dispensaries2150014656.62851.015number of hospital beds215001110350.702226.806number of health facility beds2150-9138-0.074422.736maternal and child health aids2150-932099.06122.702number of nurses215023314976.61308.48number of rmas2150-915461.76353.14number of medical assistants2150-915254.81454.941number of medical officers2150-920754.91284.897number of dentists2150-99520.23342.074number of doctors2150-93111.51212.952number of pharmacists2150-9386.814.604number of government hospitals2150-94511082834450number of vol agency hospitals2150-968167218312650number of parastatal hospitals2150-915715622number of other hospitals2150-9160255total hospitals2150-9134.3584.897number of government hospital b2150-91110224.079209.94number of vol agency hospital b2150-9840111.726184.521number of parastatal hospital b2150-9141-5.13520.835number of other hospital beds2150-9723.81422.46number of total hospital beds215001110354.66224.847number of government health cen2150-923115239384433586875number of vol agency health cen2150-919911125number of parastatal health cen2150-9165150number of other health centers2150-921015number of total health centers2150014119233344484586875number of health center beds2150-921075.82862.019number of vol agency health cen2150-945-8.1535.163number of parastatal hc beds2150-918-2.72111.433number of other health center b2150-9215number of total health center b2150-921079.41467.479number of government dispensari2150-95629.80918.693number of vol agency dispensari2150-9279.18111.528number of parastatal dispensari2150-9427.2720.123number of other dispensaries2150-91361721355841150number of total dispensaries2150014656.71250.963nat. Bank of comm. Branches2150-9215.8888.661nat. Bank of comm. Agencies2150-91900112321nat. Banks of comm. Mobile ser.2150-9215tanzania housing bank2150-911602147350cooperative rural development b2150-9100-7.61410.623distance (km) from dar es salaa2150-91850531.326606.611population : dispensary ratio2150-91126115936.6715323.889population : health center rati2150-921406740389.05646468.89saving and credit societies2150-912027.91251.932estimated council revenues, 1992150-917752360042873546.56357715512.12actual council revenues, 19912150-915712427029926000.10243273919.023estimated council revenues, 1992150-932118730055918665.88477921232.612actual council revenues, 19922150-9733510481205999387.633295205001.163estimated council revenues, 1992150-91420720900411865192.163569506904.337actual council revenues, 19932150-91020364485271359156.33418713518.202District name2150ARUMERA_RURAL1ARUMERU_RURAL1ARUSHA_URBAN4BABATI_RURAL1BAGAMOYO_RURAL2BARIADI_RURAL2BIHARAMULO_RURAL1BUKOBA_RURAL2BUKOBA_URBAN1BUNDA_RURAL1CHUNYA_RURAL1DODOMA_RURAL2DODOMA_URBAN4GEITA_RURAL4HAI_RURAL2HANANG_RURAL1HANDENI_RURAL3IGUNGA_RURAL2ILALA17IRAMBA3IRINGA_RURAL1IRINGA_URBAN5KAHAMA_RURAL2KARAGWE_RURAL2KASULU_RURAL2KIBAHA_RURAL2KIBONDO_RURAL2KIGOMA_URBAN1KILOMBERO_RURAL1KILOSA_RURAL2KILWA_RURAL1KINONDONI16KONDOA_RURAL2KWIMBA_RURAL1KYELA_RURAL2LINDI_RURAL2LINDI_URBAN1LUDEWA_RURAL1LUSHOTO_RURAL3MAFIA_RURAL1MAGU_RURAL2MAKETA_RURAL1MANYONI_RURAL1MASASI_RURAL3MASWA_RURAL1MBEYA_RURAL3MBEYA_URBAN5MBINGA_RURAL2MBOZI_RURAL1MBULU_RURAL1MEATU_RURAL3MONDULI_RURAL1MOROGORO_RURAL1MOROGORO_URBAN4MOSHI_RURAL1MOSHI_URBAN5MPANDA_RURAL2MPWAPWA_RURAL2MTWARA_RURAL2MUFINDI_RURAL1MUHEZA_RURAL2MULEBA_RURAL2MUSOMA_URBAN3MWANGA_RURAL1MWANZA_URBAN7NACHIGWEA_RURAL1NEWALA_RURAL2NGARA_RURAL1NZEGA_URBAN1ROMBO_RURAL1RUFIJI_RURAL1RUNGWE_RURAL1SAME_RURAL1SENGEREMA_RURAL1SHINYANGA_RURAL2SHINYANGA_URBAN1SINGIDA_URBAN2SONGEA_RURAL2SONGEA_URBAN1SUMBAWANGA_RURAL2SUMBAWANGA_URBAN1TABORA_RURAL1TABORA_URBAN3TANGA_URBAN5TARIME_URBAN2TEMEKE17UKEREWE_RURAL1ULAYA_RURAL1URAMBO_RURAL2household specific weight5184042.1674318.038831.9718.191household number51840100099204746.3032511.863interview month5184014526231982310978111035121665interview day51840-93116.7888.687result code51840-940-62142092933quality of interview51840-943-6215046293cluster code5184012009552111057106079.67812070901.941region code5184015511.62910.526type of cluster518401213522922368459district code51840120549.73156.363ward/village code23662818126211.56833.728time to fetch water299140-92504.15111.362household number299140100099204548.3772482.497respondent id code: section 1a299140-6161.6311.528id code2991401324.1562.933sex299140-93114600215311relationship to head299140-9133.1272.201in residence299140-91211.3642.485away at school299140-996-6581501229259hh member test299140129914age299140-912020.22917.608marital status299140-9577-63004191462252326143665641618637reading299140-9682-81-65116240212986writing299140-9690-63115644213577arithmetic299140-9695-64115863213352ever school299140-9686-82-623117044212159schooling299140-9223.1334.897primary299140-921-3.4725.016secondary299140-921-8.1612.93time unit299140-918057-619651571324179owns a watch?299140-9681-6615488223739owns a bicycle?299140-9640-6611829227439owns shoes?299140-9627-6512481424468owns any book?299140-9639-82-6819964219301owns a radio/cassette?299140-9635-6411557211053316665owns a camera?299140-9633-61071309228865expenditure on health299140-915000003042.23517040.663economic activity299140-9178.0975.303id code702602325.4712.419household number70260100099194498.0662465.831father living here70260-911523621789father's id code70260-913-1.5674.441father alive70260-95210-816-618112082574father's schooling70260-922-5.5356.669mother living here70260-929-631563421360mother's id code70260-919-0.04684.694mother alive70260-95593-84-646111022281mother's schooling70260-922-6.4315.569respondent id code: section 1b70260-6161.6751.592why no school?67080-6139-84A607AB12ABG1AC3ACG1ACK1ACL1AD4ADG1AE1AG16AGM2AGU1AGV1AHI1AJ6AK1AM4AMG3AN2AV6AVJ1B73BG1BM1BQ2C41CE1CG2CGM2CJ2CQ1CV1D540DA8DAM1DAV1DG14DGH7DGV1DH1DHG1DK1DM1DN2DV4E34EC2EG1EJ2ELJ1EV2F1792FEK1FG11FGH1FHG1FJ2FK2FL1FN3G1382GA7GDH1GH399GHI3GHJ1GHL1GHM7GHV9GI2GJ2GJK1GK6GL1GM9GN1GT1GU1GV12H247HG3HKG1HV1I31IA1J81JKV1JL1JV1K49KL2KM1KV2L27LF1LJ1LM2LV1M177MGH1MV1N209NC1ND1NF1NV1O2OCB1Q33R5RM1S36SA1SB3ST1SV3T77TD1TGH2TK1TKG1TS2U23UV1V204VA1VE1VG3VGD1VGH1VH2VJ1VJE1VK1VL2VS2VZ1X170XV1Y33Z13school distance125190-9200044.553157.083misses months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 miss school?12660-626-826A31AB1B7BJ1C4E14EA1F5G14GH4H21HG2HK1I2J3JK1K26KN1L6LK1M1N894NE2NH2NK2NS1NT8NV1NW3OG3P1R5RX3S10T46TU2U20V17W25WJ1X21attended 12 months1251901594826571year started school125190-91992633.789929.029year stopped school125190-91993640.131935.461breaks in school125190-98420-812-645174223300go back to school125190-95794-85-6381232324359did final examination?125190-98262-81-643136622551selected for further studies?125190-98823-821-660121523367333when started school?125190-91993922.813996.819any school breaks125190-96598-88-611149525407school type125190-96595-81-6712692468235704515661743845913102071129operator of school125190-96788-81-671526421503261448government assistance125190-911979-827-6490111212lives in compound125190-96812-83-67151422555distance code125190-96948-84-626813621468332594536food before school125190-96768-890-6101379621855food during school125190-96759-820-6914385270231104467547620expenditure on contributions125190-9120000296.2951895.32expenditure on school uniforms125190-960000904.1992259.012expenditure on books/supplies125190-970000444.5811870.269expenditure on transport to sch125190-987360268.1562412.055expenditure on school food/boar125190-9135000149.7362110.237expenditure on registration fee125190-9312000356.2424252.842other school expenses e.g. exam125190-945000124.7311632.576other school expenses e.g. tuit125190-960000276.2342176.169total school expenses125190-97000001782.39311615.538sponsorship125190-96621-81-612142925456type of sponsor125190-912093-81-691168211831947652669sponsor - contributions125190-930000-3.141281.495sponsor - uniforms125190-92000020.232389.702sponsor - books/supplies125190-910000-1.451182.126sponsor - transport125190-924000-5.436231.056sponsor - food/board125190-924000-6.602216.351sponsor - registration fees125190-96000014.222862.374sponsor - other fees125190-98000-5.212144.695sponsor - other expenses125190-910000-3.633172.489sponsor - total125190-9300000256.215927.347tutored?125190-96610-811-67165125240type of teacher125190-911858-84-671512257463518tuition cost for household125190-977000340.1432724.324tuition cost for others125190-9275007.789435.448sponsorship125190-96697-83-68162225189type of sponsor125190-911875-82-6141921047558662714why sponsorship125190-911880-82-613119211359143value of sponsorship125190-960000-1.988546.483other support125190-96694-83-629112825665value of other support125190-99000054.9591583.871respondent id code: section 1c125190-6161.7341.628household number125190100099194548.0712480.08id code1251901325.4032.737considered private school?125190-98824-85-6781122322389misses school125190-96767-866-61011052114334428time since illness/injury began51750-93653.7689.154first health facility distance51750-9150039.559133.343first health facility wait time51750-948-2.3155.145first health facility visit amo51750-9180000224.7212710.885second health facility distance51750-91000-1.99252.399second health facility wait tim51750-930-8.1222.829third health facility distance51750-9750-8.42114.671third health facility wait time51750-972-8.9051.445id code517501273.4862.598illess/injury code51750-91-898-6214914215337time unit51750-9115-694316654260755176177days of illnes/injury51750-9730028.157237.074day with no usual activity51750-9584010.19135.141any on consulted51750-9118-641339721656did something at?51750-93481.62820.742why no treatment51750-9104-5.2366.02expenditure on illness/injury51750-930000109.432700.655first health facility51750-91654-613008110632314317044395144619715867918first health facility type51750-91793-61611853240131011483518first health facility distance51750-91811-81-61461232602321454447first health facility practitio51750-912-1.3845.657first health facility drugs/sup51750-91674-81-6151128732476first health facility drugs amo51750-992000527.8452731.515second health facility51750-94696-660711072133101475192637883194second health facility type51750-94709-65110624133074453second health facility distance51750-94710-619122903287467second health facility practiti51750-912-7.7863.922second health facility visit am51750-91600024.236443.549second health facility drugs/su51750-94698-661444227second health facility drugs am51750-950000122.3721339.223third health faci ity51750-95132-62112243942568791third health facility type51750-95133-611182631651third health facility distance51750-95133-622732449third health facility practitio51750-95133-611152237426696101112third health facility visit amo51750-95000-7.48271.356third health facility drugs/sup51750-95133-81-6313523third health facility drugs amo51750-910000-1.603215.587total transport cost51750-9200000240.4833265.889nights admitted51750-91460-2.15626.307places admitted51750-923-0.9326.119employer/insurance?51750-91701-81-6208117723088employer/insurance amount51750-94800045.6421039.468outside help51750-91719-620818523163outside amount51750-97500061.0221400.438any part to be paid?51750-94972-6107113283amount to be repaid51750-9700-8.28917.797source of own funds51750-912-2.095.351long term problems51750-9428-82-63192023822household number51750100099204688.6972582.398respondent id code: section 1d51750-6161.6231.416antenatal health facility dista71890-91200-2.40153.008antenatal wait time71890-920.2-7.9693.098delivery health facilty distanc71890-91200-5.49335.052family planning distance71890-910000.85965.032household number71890100099204664.3562478.896id code718901273.6582.83given birth?71890-918-6251501022136children ever born71890-9160.236.459children died71890-913-2.2394.575infant deaths71890-95042-6220074718232243376426596281birth last 12 months?71890-92157-630175724245born alive?71890-96429-6111734215still alive?71890-96444-6101719216baby id code71890-934-7.6584.291month born71890-912-7.3824.878year born71890-91993187.615595.784months pregnant71890-96441-6101179821959710110any antenatal consultation?71890-96426-6121728223month at first antenatal consul71890-912-7.4814.626year at first antenatal consult71890-91993190.363599.44treated antenatal at71890-91478-7.45118.237why no antenatal care?71890-97161-6611322325382antenatal expenditure71890-99000-6.645119.212antenatal health facility71890-96449-6101128249316843806174antenatal health facility type71890-96455-69161226834045antenatal facility distance cod71890-96459-6431529634804106antenatal practitioner71890-96451-69178258033541951391113antenatal visit amount71890-94000026.463817.968antenatal drugs/supplies71890-96452-61715802140antenatal drugs/supplies amount71890-94500015.606658.577antenatal transport cost71890-92000017.011419.34delivery health facility71890-96421-61413412323844486472368198delivery health facility type71890-96671-61214282563184252delivery facility distance code71890-96665-649112453355474delivery practitioner71890-96433-6819824193114125487181691010211131delivery by caesarian operation71890-96426-6101602693delivery visit amount71890-94000037.246854.147delivery drugs/supplies71890-96427-61813952349delivery drugs/supplies amount71890-94000021.663704.739delivery transport costs71890-92950085.868801.528delivery nights admitted71890-984-7.8454.016delivery employer/insurance71890-96425-6131182733delivery employer/insurance amo71890-9400001.517523.357prenatal/delivery outside help?71890-96429-6141312715prenatal/delivery outside amoun71890-9100002.831256.625prenatal/delivery repay?71890-97142-6413240prenatal/delivery repay amount71890-95000-7.58576.274prenatal/delivery source of own71890-96432-6171410220384715231current family planning71890-995-874-621246124557family planning method71890-985-4.3366.998family planning health facility71890-94723-6130155912602693187431252161271381793family planning distance code71890-96301-6571421513606470family planning practitioner71890-96287-691109265934541552618839221120family planning visit costs71890-97000010.557835.579family planning transport costs71890-92000016.013388.255family planning medicines/tests71890-93000031.34531.932respondent id code: section 1e71890-6161.9951.703family planning facility type71890-6716612132dispensary/health centre distan51840-9150051.395150.816government hospital distance51840-9150032.05885.689mission hospital distance51840-9100018.76660.6mission health centre distance51840-9160061.939161.02respondent id code: section 2a51840-9151.5681.306trial 1n: needed drugs availabl51840-9205.2132.312trial 1n: qualified doctors/nur51840-9204.5372.07trial 1n: facility in village o51840-9203.2972.085trial 1n: good environment/faci51840-9203.1081.823trial 1n: health-promotion acti51840-9203.7532.09trial 1n: quality of response51840-64514980212432946trial 1r: needed drugs availabl51840-923-621937288931567410475719trial 1r: qualified doctors/nur51840-925-6311115213023152848475364trial 1r: facility in village o51840-925-621241921361388043305167trial 1r: good environment/faci51840-9251248821561373842595113trial 1r: health-promotion acti51840-924-6111866214823111144985202trial 2n: needed drugs availabl51840-916-8.62.375trial 2n: qualified doctors/nur51840-916-8.6172.293trial 2n: facility in village o51840-950400221622033842152261184trial 2n: good environment/faci51840-95040015172233334305166107584101trial 2n: health-promotion acti51840-9504001715215323434526613758391102trial 2n: quality of response51840-9504211372431trial 2r: needed drugs availabl51840-95042131222350426513trial 2r: qualified doctors/nur51840-9504212724134742057trial 2r: facility in village o51840-950421642413264754trial 2r: good environment/faci51840-9504316224432041451trial 2r: health-promotion acti51840-95042148245325414510health form number51840-634122462182731077respondent id code: health form51840-915-4.0815.09trial 1: pay for treatment 600051840-92926-612160221644trial 1: pay for treatment 160051840-94572-61012772325trial 1: pay for treatment 800051840-94850-6101862238trial 1: pay for treatment 120051840-95095-64120265trial 1: pay for treatment 10051840-93540114082236trial 1: pay for treatment 400051840-93784118521215trial 1: pay for treatment 100051840-9396915422673trial 1: pay for treatment 200051840-94643-6711962338trial 1: quality of response51840-92955-612122052537trial 2: pay for treatment 600051840-95179-6322trial 2: pay for treatment 160051840-95184trial 2: pay for treatment 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income 8000051840-9518311trial 2: required income 10000051840-95184trial 2: required income 18000051840-95184trial 2: quality of response51840-95182-6111household number51840100099204746.3032511.863code for the shamba/garden75860A3417B2128C1128D524E221F93G39H18I8J5K3L2shamba/garden size75860-91001.8473.765household number75860100099194013.8452299.888shamba/garden size code75860-9354-612168072413shamba/garden owner75860-921-6212602242353710416shamba/garden owner id code75860-94973-6601238821203741055637108693101shamba/garden owner id code75860-97049-656162452344156627485101shamba/garden how acquired75860-9698-64111245236322164285154363417143088shamba/garden quality75860-922-6619692438632203shamba/garden rent in75860-931-647136927139shamba/garden rent out75860-932-61915727478respondent id code: section 3a/75860-6814997221403954955646547608269171019116125Shambas/gardens: # owned by hou7586004791135621888316494106756296234714887299102011111224Shambas/gardens: # used by hous75860065401582222531404865588Shambas/gardens: number owned/u7586007559115243444Total shambas/gardens: owned an758600141129021994318154121856366312714789699102011111224code for livestock46650A736B96C490D54E202F278G831H140I1753J39K43L3household number46650100199193573.1952103.55respondent id code: section 3a/46650-6613091212253724505356507448319201035112124livestock: sold any?46650-915-6141104723589livestock: bought any?46650-916-624162024005livestock: number born46650-97004.80716.897livestock: number eaten46650-94002.1459.377livestock: number lost46650-92002.6558.346livestock: current number46650-91500012.298220.566livestock: number sold46650-9110008.657236.048livestock: number bought46650-9120004.919187.197economic activities: code for i2299002161536.42425.308economic activities: importance229900-9992.5045.101economic activities: sales for229900-999-3.3576.979respondent id code: section 3b229900-6151.5461.24household number229900100099204234.3122351.896expndtrs: code for item131564062141102.66423.432expndtrs: payment in cash1315640-950000005140.93741654.406expndtrs: payment in kind1315640-9500000280.7493690.117expndtrs: given as gift/loan1315640-95000000193.31114719.175rspndnt id code: section 3c&3d1315640-6151.5661.153household number1315640100099204947.1372523.651building64550A5181B887C248D85E26F13G7H4I2J2household number64550100099204432.6792488.284type of housing64550-9101328821233172841211595number of buildings64550-6511426221263348542365656367218161020building: windows64550-911-661169280034229413253226786building: number of rooms64550-9152.7671.624building: how long: years64550-87910.1629.995building: how long: months64550-8201.913.113building: owner64550-950-84-69146412144368423551304building: rent value: amount64550-95000002890.33514289.544building: rent value: time64550-92138-620341554047652building: rent payment: amount64550-9765000909.51311896.296building: rent payment: time64550-94857-81-61324251429634respondent id code: section 3f/64550-6151.6111.297building: walls64550-6131244412272892112315420951113546156261177611654171350761building: floors64550-65137561461772223224259541151661976building: roof64550-63125311224123613371422402343101312322341434734125107655748817source of drinking water: dista51840-9303087.758174.173water bill in rainy season: amo51840-95000-4.33290.101water bill in dry season: amoun51840-95000-2.847109.616distance to public road51840-9300097.914169.507time to public road51840-97005.27515.999distance to farm produce market51840-9250016.116106.838time to farm produce market51840-9150-4.11611.21distance to animal market51840-91200-2.41536.51time to animal market51840-9400-6.1999.949distance from food market/shop51840-91600108.666194.866time to reach the market/shop51840-94007.42513.252time for last water bill: amoun51840-9500-5.4358.605respondent id code: section 3f/51840-6101317721743353456535635730822991010112122source of drinking water51840-9126.4933.029amount for last water bill51840-9100000216.2481781.196time for last water bill: unit51840-93475-86-647326641051356624sold water?51840-93063-64213022049proportion of water sold51840-95138-61619293745source of drinking water: dista51840-9906-6141337942092514286238buys water?51840-933-63145424694water bill in rainy season: uni51840-94814-81-66611442117332410water bill in dry season: unit51840-94720-81-63611942186337410does household have a toilet?51840-95-61149002278type of toilet51840-629713752450834is there electricity in village51840-95-621280222375source of electricity in the ho51840-9123.9151.838source of light in the home51840-96-63111296237883941553type of cooker51840-9241.681.278type of cooker51840-952-5.3855.926distance to public road: code51840-966-81-612937424300151147698time to public road: unit51840-998-61031462223363646513type of public road51840-911-621285428523146441months public road is passable51840-91211.2512.169public transport on road?51840-97-621327921896own television/video?51840-97114725030own refregerator/deep freezer?51840-910-63134324828sold farm produce/livestock in51840-97-611204323133distance to farm produce market51840-93123-6493264302573861317815time to farm produce market: un51840-93947-644185023363641transport to farm produce marke51840-93933-84-650110472553194257371state of road to farm produce m51840-93937-86-64418372360distance to animal market: code51840-93590-815-63838430560661607737time to animal market: unit51840-94337-812-63712172562319transport to animal market51840-94240-8106-6351669236324458874state of road to animal market51840-94093-8238-63814772338buy outside for sale in village51840-81-6301109024063employ any one for farming or b51840-921-61158924573employ for how many days in a y51840-93655.83764.953rented a shamba to pay in kind?51840-915-62119024977own a bank account?51840-918-83-71-631148123678help to any one outside the hou51840-921-6101250422649how much help given last year?51840-95000008847.32425672.015where buy food frequently?51840-9328-6651323429703784492517distance from food market/shop:51840-9557-681326841965520826231days market/shop is open51840-9357827.028207.817which days are for shopping?51840-9571335.018218.345how do you reach the market/sho51840-97321.38222.169time to reach the market/shop:51840-9595-6291395725913844cost to reach the market/shop51840-9500014.872155.054which religions are followed?51840-92312.6726.388household number51840100099204746.3032511.863what tribes are household membe51840-920673.80548.796what tribes are household membe51840-92059.45540.574what tribes are household membe51840-9204-7.99510.997what tribes are household membe51840-9145-8.8464.024what tribes are household membe51840-962-8.9761.129id code3290A302B18C5D2E2sex3290-6411562169relationship to head of househo3290-6165.4623.422age at death: years3290-99829.6628.517age at death: months3290-914-0.2224.774live children left in household3290-985-6421982104id codes for left children3290-9228-6213523737445264728293102111id codes for left children3290-913-7.4384.381id codes for left children3290-9307-614165172101111id codes for left children3290-913-8.4042.933id codes for left children3290-9319-6169id codes for left children3290-9323-6175id codes for left children3290-9325-6282was diseased head of household?3290-989-6411342165cause of death3290-92129021231541516177household number3290100699194258.4952279.738respondent id code: section 3g3290-61121828937455262718292105-16 ?7720A550B72C108D42total chairs in 4 rows each 127560A168B69C438D81highest of 0.1, 0.01, 0.111, 0.7760A126B51C98D5011% of 4007610A54B293C185D229height of a man7670A79B354C153D18112 km x 3 trips to and fro7700A188B423C90D692/3 of 3007490A99B202C236D212square root of 227580A151B164C222D2212a+b^2 (if a -3 and b 3)7510A69B211C234D237what is x if 2x-3 17?7040A152B188C170D194what is sold in the market?7730A51B621C20D81what was approaching?7650A44B553C74D94what was the boat full of?7680A25B151C32D560what animal accompanied the man7710A63B89C583D36what was inside the house?7630A494B31C187D51the man is said to be?7700A630B32C73D35respondent id code: section tes808011623531004136515161377988669321015114122133143152164172181211household number8080102598994801.4492407.728maize flour: unit740-62.751.75 KG11KG1BAG1BAKULI1DEBE2KG59KIBABA2KILO1KOPO1PISHI2maize flour: conversion factor1040-950-5.3756.486maize grain: unit7801.25 KG1100 KGS11KG1BAG2DEBE15GUNIA1KG9ONE TIN1PISHI4SAHANI1TIN41TIUN1maize grain: conversion factor1040-91007.04115.557maize grain: price per kg1040-913942.63537.525rice: unit950.7511 KG31KG1BAKULI1BEULO1KG82KILO1PISHI4SAHANI1paddy: unit340-6460 KGS1BAG2BAKULI2BEULO1DEBE6GUNIA5KG3KOPO1PISHI3TIN6paddy: conversion factor1040-91000.55819.509wheat flour: unit8201 KG21KG2DEBE1KG76TIN1millet flour: unit80-64BAKULI1KG3millet: unit550-64.75 KG1100KGS15 KG TIN1BAG2BAKULI2DEBE7GUNIA2KG23TIN11TINTIN1millet: price per kg1040-918545.14359.482sorghum flour: unit60-64BAKULI1KG1sorghum: unit220-64BAG1DEBE5KG6SAHANI1TIN5sorghum: price per kg1040-980013.41584.288cassava: unit820-64111 KG11.50150 KG1BUNDLE4DEBE3FUNGU13FUNGU 31FUNGUS1GUNGU1HEAP38KG11TENGA1TIUN1cassava: conversion factor1040-650-0.6447.113cassava: price per kg1040-920051.93945.239beans (dry): unit1010.751.75 KG11 KG11KG2BAG1BAKULI3BEULO1DEBE3KG77KIBABA2KOPO1PISHI3SAHANI1TIN4beans (dry): conversion factor1040-9100-3.19512.332cattle meat: unit9101 KG21KG2KG87fish (fresh): unit630-62.50 EACH1111 KG21 PIECE231KG1EACH1FUNGU2FUNGUS1KG20ONE1PIECE7VITUHI 11fish (fresh): conversion factor1040-61-3.7333.132fish (dry): unit820-62.125 FUNGU1.25 KG1.501131 FISH11 KG11 PIECE6313 PCS1BUNDLE1DO8EACH2FUNGU7FUNGUS1GEGE 11KG31ONE1PC1PC GEGE1PEREGE 101PIECE8VITUHI 51fish (dry): conversion factor1040-920-3.3034.176paraffin/kerosene: unit1030-61.25 LITRE1.5011 LITRE25 LITRES5CHUPA ORNG1CHUPA SODA1FANTA BOTT8FAULABOTTB1GALLON3KIBABA3KIJIKO1KOPO5KOROBOI1KORRBOI1KOTA2LITRE59LTR5SODA BOTTL2paraffin/kerosene: conversion f1040-920-3.46.691paraffin/kerosene: price per kg104080600191.23192.553sugar: unit1000.5011 KG21KG2KG95cooking oil: unit990-611 GALLON11 KG12 LTR13 GALLON13 LITRES1BEER BOTTL1BOTTLE1BOTTLE SOD1CHUPA ORNG1GALLON2KIBABA2KIJIKO1KIKOMB1KOPO8KOROBOI11LITRE52LIYRE1LTR5ORANGE3ORNG BOTTL1SODA BOTTL1UMPA SODA1cooking oil: conversion factor1040-920-1.9228.37cooking oil: price per kg1040-61000544.708252.037matches: unit9301 BOX241 UNIT4BOX21EACH10EACH BOX1ESCH1KG1PC6PIECE24PIECEP1bicycles: unit700-61111 UNIT4EACH1ONE11PC2PHOENIX44PIECE1SWALA5bicycles: price per kg1040-95500026314.85619992.098hoes/jembe: unit750-61111 INIT11 UNIT2EACH14NGWAMBA1ONE16PC11PIECE28maize flour: price per kg1040-926088.67372.397rice: conversion factor1040-920-6.1253.364rice: price per kg1040-9300195.17371.819paddy: price per kg1040-92002655.705wheat flour: conversion factor1040-920-6.2883.326wheat flour: price per kg1040-6310191.673105.575millet flour: conversion factor1040-924-67911millet flour: price per kg1040-9180-1.96225.478millet: conversion factor1040-91001.65421.817sorghum flour: conversion facto1040-924-67911sorghum flour: price per kg1040-9100-4.96213.5sorghum: conversion factor1040-9100-3.58712.211beans (dry): price per kg1040-6400205.61599.098cattle meat: conversion factor1040-924-680cattle meat: price per kg1040-91200472.067318.992fish (fresh): price per kg1040-91500182.327247.188fish (dry): price per kg1040-93000343.144388.416sugar: conversion factor1040-924-680sugar: price per kg10401201150456.346314.86matches: conversion factor1040-924-680matches: price per kg1040154024.0385.534bicycles: conversion factor1040-924-680hoes/jembe: conversion factor1040-924-680hoes/jembe: price per kg1040-92300931.625671.643cluster code1040120275521110519079618.33719988352.192maize flour: unit price1040-95000154.654508.32maize grain: unit price1040-97000803.3851098.598rice: unit price1040-9650210.25104.763paddy: unit price1040-910000665.6061870.826wheat flour: unit price1040-62000223.788247.017millet flour: unit price1040-9180-1.96225.478millet: unit price1040-913000653.0771947.223sorghum flour: unit price1040-9100-4.96213.5sorghum: unit price1040-96000136.837625.998cassava: unit price1040-9120076.462173.25beans (dry): unit price1040-615000498.2021536.899cattle meat: unit price1040-91200469.125321.991fish (fresh): unit price1040-91500139.462241.925fish (dry): unit price1040-93000232.519365.519paraffin/kerosene: unit price1040-61000192.49201.252sugar: unit price1040-61150445.788324.162cooking oil: unit price1040-62000501.096426.103matches: unit price1040154024.0385.534bicycles: unit price1040-95500026314.85619992.098hoes/jembe: unit price1040-92300931.625671.643Region Code104025520.94218.41supervisor id code1040-910214424327526